Temporal Registration of Cardiac Multimodal Images Using Locally Linear Embedding Algorithm

Purpose: Multimodal Cardiac Image (MCI) registration is one of the evolving fields in the diagnostic methods of Cardiovascular Diseases (CVDs). Since the heart has nonlinear and dynamic behavior, Temporal Registration (TR) is the fundamental step for the spatial registration and fusion of MCIs to integrate the heart's anatomical and functional information into a single and more informative display. Therefore, in this study, a TR framework is proposed to align MCIs in the same cardiac phase. Materials and Methods: A manifold learning-based method is proposed for the TR of MCIs. The Euclidean distance among consecutive samples lying on the Locally Linear Embedding (LLE) of MCIs is computed. By considering cardiac volume pattern concepts from distance plots of LLEs, six cardiac phases (end-diastole, rapid-ejection, end-systole, rapid-filling, reduced-filling, and atrial-contraction) are temporally registered. Results: The validation of the proposed method proceeds by collecting the data of Computed Tomography Coronary Angiography (CTCA) and Transthoracic Echocardiography (TTE) from ten patients in four acquisition views. The Correlation Coefficient (CC) between the frame number resulted from the proposed method and manually selected by an expert is analyzed. Results show that the average CC between two resulted frame numbers is about 0.82±0.08 for six cardiac phases. Moreover, the maximum Mean Absolute Error (MAE) value of two slice extraction methods is about 0.17 for four acquisition views. Conclusion: By extracting the intrinsic parameters of MCIs, and finding the relationship among them in a lower-dimensional space, a fast, fully automatic, and user-independent framework for TR of MCIs is presented. The proposed method is more accurate compared to Electrocardiogram (ECG) signal labeling or time-series processing methods which can be helpful in different MCI fusion methods.

The 3D-atlas builder: a dynamic and expandable 3D-tool for monitoring the changes in the neuronal differentiation domain during hindbrain morphogenesis

Reconstruction of prototypic three-dimensional (3D) atlases at the scale of whole tissues or organs requires specific methods to be developed. We have established a protocol and provide experimental proof for building a digital 3D-atlas (here, for zebrafish hindbrain) that integrates spatial and temporal data for neuronal differentiation and brain morphogenesis, through a combination of in vivo imaging techniques paired with image analyses and segmentation tools. First, we generated a reference 3D hindbrain from several imaged specimens and segmented them using a trainable tool; these were aligned using rigid registration, revealing distribution of neuronal differentiation patterns along the axes. Second, we quantified the dynamic growth of the neuronal differentiation domain vs. the progenitor domain in the whole hindbrain. Third, we used in vivo Kaede-photoconversion experiments to generate a temporal heatmap of the neuronal growth in the whole hindbrain, revealing the spatiotemporal dynamics of neuronal differentiation upon morphogenesis. Last, as proof-of-concept, we assessed the birthdate order of GABAergic-neurons using our temporal registration map. As this protocol uses open-access tools and algorithms, it can be shared for standardized and accessible tissue-wide cell population atlas construction.

SENTINEL-2 GLOBAL REFERENCE IMAGE VALIDATION AND APPLICATION TO MULTITEMPORAL PERFORMANCES AND HIGH LATITUDE DIGITAL SURFACE MODEL

In the frame of the Copernicus program of the European Commission, Sentinel-2 is a constellation of 2 satellites with a revisit time of 5 days in order to have temporal images stacks and a global coverage over terrestrial surfaces. Satellite 2A was launched in June 2015, and satellite 2B will be launched in March 2017.<br><br> In cooperation with the European Space Agency (ESA), the French space agency (CNES) is in charge of the image quality of the project, and so ensures the CAL/VAL commissioning phase during the months following the launch. This cooperation is also extended to routine phase as CNES supports European Space Research Institute (ESRIN) and the Sentinel-2 Mission performance Centre (MPC) for validation in geometric and radiometric image quality aspects, and in Sentinel-2 GRI geolocation performance assessment whose results will be presented in this paper. The GRI is a set of S2A images at 10m resolution covering the whole world with a good and consistent geolocation. This ground reference enables accurate multi-temporal registration of refined Sentinel-2 products.<br><br> While not primarily intended for the generation of DSM, Sentinel-2 swaths overlap between orbits would also allow for the generation of a complete DSM of land and ices over 60° of northern latitudes (expected accuracy: few S2 pixels in altimetry). This DSM would benefit from the very frequent revisit times of Sentinel-2, to monitor ice or snow level in area of frequent changes, or to increase measurement accuracy in areas of little changes.